Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease

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Abstract

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  1. SciScore for 10.1101/2020.03.27.20044891: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    As any model, we have made important assumptions that could overestimate the effect of the interventions (see limitations below). Quantifying the short-term impact of an intervention is very important since it allows decision makers to estimate the immediate number of resources needed and to plan for further resources in the long term. However, our simulations suggest that even in the more optimistic scenario, where all the age groups reduce their contact rates over 85%, the epidemic is set to rebound once the social distancing interventions are lifted. Our results suggest that social distancing interventions can “buy us” several weeks that could prove to be essential to strengthen our health systems and restock medical supplies, but will fail to mitigate the current pandemic. This is in agreement with other modeling results which suggested that very long periods of social distancing would be needed to control transmission [20]. Yet, sustaining social distancing interventions over a period of several months might not be feasible, both economically and socially. A combination of social distancing interventions with testing, isolation and contact tracing of new cases is needed to suppress transmission of SARS-CoV-2 [30]. Further, these interventions need to happen in synchrony around the world, as a new imported case could spark a new outbreak in any given region. Furthermore, our results highlight the importance of the timing of social distancing interventions relative to the ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.